Is AI ready to be a mid-level engineer?

As someone building AI developer tools and studying their real-world implementation, I believe this fundamentally misunderstands both the current state of AI and the role of mid-level engineers.

Current AI coding assistants excel at specific tasks: generating boilerplate, explaining code, and helping with routine programming tasks.

But there’s a crucial gap between writing isolated functions and understanding complex systems. In our testing, even the most advanced AI tools consistently fail when dealing with interconnected systems. They’ll generate syntactically perfect code that introduces subtle runtime errors by missing critical system dependencies.

Look, AI coding tools are already impressive. Companies like Lovable and Bolt (both $4M+ ARR) are showing real value. But they’re thriving in a completely different space: helping indie developers build from scratch, assisting with smaller projects, turning non-developers into casual coders.

In building our own AI developer tools (and surveying 87 developers about their experiences), I’ve identified three fundamental challenges that separate AI from mid-level engineers:

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